Using Web Search Logs to Identify Query Classification Terms

Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interfaces

Raising awareness of traffic pollution: the potential benefits and problems of using a warning smell

Exposure to traffic pollution is increasing worldwide as people move to cities, and as more vehicles join the roads, creating longer journeys and more traffic jams. Most traffic pollutants are odourless and invisible, which hides exposure from the public. If traffic pollution had a distinctive smell it would enable people to avoid exposure, and increase the political will for difficult policy changes. A smell may also instigate longer-term changes, such as switching to active transport for school pick-ups. A smell could be added using a fuel additive or a temporary device attached to vehicle exhausts.

Raman spectroscopy of the multi-anion mineral schlossmacherite (H3O,Ca)Al3(AsO4,PO4,SO4)2(OH)6

The mineral schlossmacherite (H3O,Ca)Al3(AsO4,PO4,SO4)2(OH)6 , a multi-cation-multi-anion mineral of the beudantite mineral subgroup has been characterised by Raman spectroscopy. The mineral and related minerals functions as a heavy metal collector and is often amorphous or poorly crystalline, such that XRD identification is difficult. The Raman spectra are dominated by an intense band at 864 cm-1, assigned to the symmetric stretching mode of the AsO43- anion. Raman bands at 809 and 819 cm-1 are assigned to the antisymmetric stretching mode of AsO43- . The sulphate anion is characterised by bands at 1000 cm-1 (ν1), and at 1031, 1082 and 1139 cm-1 (ν3). Two sets of bands in the OH stretching region are observed: firstly between 2800 and 3000 cm-1 with bands observed at 2850, 2868, 2918 cm-1 and secondly between 3300 and 3600 with bands observed at 3363, 3382, 3410, 3449 and 3537 cm-1. These bands enabled the calculation of hydrogen bond distances and show a wide range of H-bond distances.

Pre-clinical evaluation of amphiphilic silicone oligomers for scar remediation

The formation of hypertrophic scars is a frequent outcome of wound repair and often requires further therapy with treatments such as silicone gel sheets (SGS; Perkins et al., 1983). Although widely used, knowledge regarding SGS and their mechanism of action on hypertrophic scars is limited. Furthermore, SGS require consistent application for at least twelve hours a day for up to twelve consecutive months, beginning as soon as wound reepithelialisation has occurred. Preliminary research at QUT has shown that some species of silicone present in SGS have the ability to permeate into collagen gel skin mimetics upon exposure. An analogue of these species, GP226, was found to decrease both collagen synthesis and the total amount of collagen present following exposure to cultures of cells derived from hypertrophic scars. This silicone of interest was a crude mixture of silicone species, which resolved into five fractions of different molecular weight. These five fractions were found to have differing effects on collagen synthesis and cell viability following exposure to fibroblasts derived from hypertrophic scars (HSF), keloid scars (KF) and normal skin (nHSF and nKF). The research performed herein continues to further assess the potential of GP226 and its fractions for scar remediation by determining in more detail its effects on HSF, KF, nHSF, nKF and human keratinocytes (HK) in terms of cell viability and proliferation at various time points. Through these studies it was revealed that Fraction IV was the most active fraction as it induced a reduction in cell viability and proliferation most similar to that observed with GP226. Cells undergoing apoptosis were also detected in HSF cultures exposed to GP226 and Fraction IV using the Tunel assay (Roche). These investigations were difficult to pursue further as the fractionation process used for GP226 was labour-intensive and time inefficient. Therefore a number of silicones with similar structure to Fraction IV were synthesised and screened for their effect following application to HSF and nHSF. PDMS7-g-PEG7, a silicone-PEG copolymer of low molecular weight and low hydrophilic-lipophilic balance factor, was found to be the most effective at reducing cell proliferation and inducing apoptosis in cultures of HSF, nHSF and HK. Further studies investigated gene expression through microarray and superarray techniques and demonstrated that many genes are differentially expressed in HSF following treatment with GP226, Fraction IV and PDMS7-g-PEG7. In brief, it was demonstrated that genes for TGFβ1 and TNF are not differentially regulated while genes for AIFM2, IL8, NSMAF, SMAD7, TRAF3 and IGF2R show increased expression (>1.8 fold change) following treatment with PDMS7-g-PEG7. In addition, genes for αSMA, TRAF2, COL1A1 and COL3A1 have decreased expression (>-1.8 fold change) following treatment with GP226, Fraction IV and PDMS7-g-PEG7. The data obtained suggest that many different pathways related to apoptosis and collagen synthesis are affected in HSF following exposure to PDMS7-g-PEG7. The significance is that silicone-PEG copolymers, such as GP226, Fraction IV and PDMS7-g-PEG7, could potentially be a non-invasive substitute to apoptosis-inducing chemical agents that are currently used as scar treatments. It is anticipated that these findings will ultimately contribute to the development of a novel scar therapy with faster action and improved outcomes for patients suffering from hypertrophic scars.

A descriptive approach for power system stability and security assessment

Power system dynamic analysis and security assessment are becoming more significant today due to increases in size and complexity from restructuring, emerging new uncertainties, integration of renewable energy sources, distributed generation, and micro grids. Precise modelling of all contributed elements/devices, understanding interactions in detail, and observing hidden dynamics using existing analysis tools/theorems are difficult, and even impossible. In this chapter, the power system is considered as a continuum and the propagated electomechanical waves initiated by faults and other random events are studied to provide a new scheme for stability investigation of a large dimensional system. For this purpose, the measured electrical indices (such as rotor angle and bus voltage) following a fault in different points among the network are used, and the behaviour of the propagated waves through the lines, nodes, and buses is analyzed. The impact of weak transmission links on a progressive electromechanical wave using energy function concept is addressed. It is also emphasized that determining severity of a disturbance/contingency accurately, without considering the related electromechanical waves, hidden dynamics, and their properties is not secure enough. Considering these phenomena takes heavy and time consuming calculation, which is not suitable for online stability assessment problems. However, using a continuum model for a power system reduces the burden of complex calculations

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Topological map induction using neighbourhood information of places

In topological mapping, perceptual aliasing can cause different places to appear indistinguishable to the robot. In case of severely corrupted or non-available odometry information, topological mapping is difficult as the robot is challenged with the loop-closing problem; that is to determine whether it has visited a particular place before. In this article we propose to use neighbourhood information to disambiguate otherwise indistinguishable places. Using neighbourhood information for place disambiguation is an approach that neither depends on a specific choice of sensors nor requires geometric information such as odometry. Local neighbourhood information is extracted from a sequence of observations of visited places. In experiments using either sonar or visual observations from an indoor environment the benefits of using neighbourhood clues for the disambiguation of otherwise identical vertices are demonstrated. Over 90% of the maps we obtain are isomorphic with the ground truth. The choice of the robot’s sensors does not impact the results of the experiments much.

Anonymity and one-way authentication in key exchange protocols

Key establishment is a crucial cryptographic primitive for building secure communication channels between two parties in a network. It has been studied extensively in theory and widely deployed in practice. In the research literature a typical protocol in the public-key setting aims for key secrecy and mutual authentication. However, there are many important practical scenarios where mutual authentication is undesirable, such as in anonymity networks like Tor, or is difficult to achieve due to insufficient public-key infrastructure at the user level, as is the case on the Internet today. In this work we are concerned with the scenario where two parties establish a private shared session key, but only one party authenticates to the other; in fact, the unauthenticated party may wish to have strong anonymity guarantees. We present a desirable set of security, authentication, and anonymity goals for this setting and develop a model which captures these properties. Our approach allows for clients to choose among different levels of authentication. We also describe an attack on a previous protocol of Øverlier and Syverson, and present a new, efficient key exchange protocol that provides one-way authentication and anonymity.

Mobile applications of focused link discovery

Interaction with a mobile device remains difficult due to inherent physical limitations. This dif-ficulty is particularly evident for search, which re-quires typing. We extend the One-Search-Only search paradigm by adding a novel link-browsing scheme built on top of automatic link discovery. A prototype was built for iPhone and tested with 12 subjects. A post-use interview survey suggests that the extended paradigm improves the mobile information seeking experience.

Female genital mutilation : legal, attitudinal and practical reform

Female genital mutilation (FGM) is a cultural practice common in many Islamic societies. It involves the deliberate, non-therapeutic physical modification of young girls’ genitalia. FGM can take several forms, ranging from less damaging incisions to actual removal of genitalia and narrowing or even closing of the vagina. While often thought to be required by religion, FGM both predates and has no basis in the Koran. Rather, it is a cultural tradition, motivated by a patriarchal social desire to control female bodies to ensure virginity at marriage (preserving family honour), and to prevent infidelity by limiting sexual desire. In the USA and Australia in 2010, peak medical bodies considered endorsing the medical administration of a ‘lesser’ form of FGM. The basis for this was pragmatic: it would be preferable to satisfy patients’ desire for FGM in medically-controlled conditions, rather than have these patients seek it, possibly in more severe forms, under less safe conditions. While arguments favouring medically-administered FGM were soon overcome, the prospect of endorsing FGM illuminated the issue in these two Western countries and beyond. This paper will review the nature of FGM, its physical and psychological health consequences, and Australian laws prohibiting FGM. Then, it will scan recent developments in Africa, where FGM has been made illegal by a growing number of nations and by the Protocol to the African Charter on Human and Peoples’ Rights 2003 (the Maputo Protocol), but is still proving difficult to eradicate. Finally, based on arguments derived from theories of rights, health evidence, and the historical and religious contexts, this paper will ask whether an absolute human right against FGM can be developed.

Engaging parents in STEM: Coteaching and cogenerative dialoguing in a Queensland high school

Diminished student interest in science, technology, engineering and mathematics (STEM) is recognised by educators, researchers and public policy makers as a concerning global trend. Inviting stakeholders like scientists and industry specialists to discuss their work is one means schools use to facilitate student engagement in the sciences. However, these visits generally comprise one-off sessions with minimal relevance to students’ particular and ongoing learning needs. This case study investigated coteaching and cogenerative dialoguing with parents in teaching a Year-8 multidisciplinary unit with science and technology foci. Two parents cotaught alongside the resident teacher and researcher over eight months. This paper concentrates on one parent, a medical scientist by profession. Data sources included video and audio recordings of cogenerative dialogues and classroom interactions, student work samples and journal entries. Data were interrogated using the sociological constructs of fields and capitals and the dialectic of structure|agency. The findings reveal how (a) the parent’s science and technology knowledge was tailored to the students’ needs initially and continually and (b) student-generated data indicated enhanced engagement in science and technology. The research speaks to schools and governments about enhancing STEM education by furthering collaborative relationships with relevant stakeholders.

Personalised search – a hybrid approach for web information retrieval and its evaluation

Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

An evaluation framework for assessing the impact of public bicycle share schemes

INTRODUCTION • Public bicycle share schemes have emerged as a method of increasing rates of bicycle riding. • The overwhelming majority of schemes have begun since 2005, taking advantage of various tracking and payment technologies making short term rental practical and affordable. • Very little research has been undertaken to determine their potentially broad impact on transport behaviour and consequently, it is difficult to understand the performance of these schemes in terms of reduced emissions and congestion, as well as possible increases in physical activity.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.